Articles tagged with #llm

What Claude Haiku 5.5 costs, what its reported benchmarks show, and how to call it from Python for cheap, high-volume classification.

Practical instrumentation strategies for measuring and allocating LLM costs in production across tenants, A/B tests, and feature flags without sacrificing latency.

Real-world prompt injection detection and mitigation for production AI systems. Trade-offs between sandboxing, filtering, and risk acceptance with concrete RAG and multi-turn examples.

Close the gap between offline benchmarks and production reality. Concrete patterns for designing evals that catch hallucinations, detect drift, and drive business decisions.

A practical framework for evaluating LLM providers and models based on token economics, latency percentiles, and cascading system design constraints—not vendor hype.